docs: def load_batch_x(path_batch,
                   flatten = False,
                   time_major = False):
      """ Loads a batch of input features given a list of paths to numpy
      arrays in that batch."""
  
      utterances = [np.load(str(path)) for path in path_batch]
      utter_lens = [utterance.shape[0] for utterance in utterances]
      max_len = max(utter_lens)
      batch_size = len(path_batch)
      shape = (batch_size, max_len) + tuple(utterances[0].shape[1:])
      batch = np.zeros(shape)
      for i, utt in enumerate(utterances):
          batch[i] = zero_pad(utt, max_len)
      if flatten:
          batch = collapse(batch, time_major=time_major)
      return batch, np.array(utter_lens)